AirflowDockerKafkaKubernetesPostgresPythonSQLVaultData EngineeringAnalyticsSnowflakedbtSource ControlSalesforceCRMAgileCI/CDProduct ManagementRemote Work
About this role
Role Overview
Build and support data pipelines that can handle the volume and complexity of data while ensuring scale, data accuracy, availability, observability, security, and optimum performance
Developing and maintaining data warehouse tables, views, and models, for consumption by analysts and downstream applications
Own and lead workstreams while driving results through self or your team
Participate in periodic data engineering activities, e.g. monthly insights reporting, profile data updates, etc
Troubleshoot production issues, and participating in on-call activities
Identify several areas for improving data engineering processes, and share with the team
Contribute consistently towards building our data platform, which includes data pipelines, and data warehouse layers
Independently own and lead workstreams whether it is periodic data engineering activities, or work items in support of our roadmap
Deepen your understanding, and build subject matter expertise of our data & ecosystem
Your contributions have led to us making significant progress in implementing the data platform strategy, and key data initiatives to support the company's growth
You’ve established yourself as a key team member with subject matter expertise within data engineering
Requirements
Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field
6+ years of experience in data engineering
Demonstrated experience of building, and supporting large scale data pipelines
streaming and batch processing
Software engineering mindset, leading with the principles of source control, infrastructure as code, testing, modularity, automation, CI/CD, and observability
Experience of working with Google Analytics, Marketing, Ad & Social media platform, CRM/Salesforce, and JSON data; Government datasets, and geo-spatial data will be a plus
Knowledge and understanding of the modern data platform, and its key components
ingestion, transformation, curation, quality, governance, and delivery
Knowledge of data modeling techniques (3NF, Dimensional, Vault)
Self-starter, analytical problem solver, highly attentive to detail, effective communicator, and obsessed with good documentation
Familiarity with Agile product management principles will be a plus